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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineering Software Developer - **Company:** TDI LLC - **Location:** United States - **Experience:** Expert - **Salary:** $130,000.0 - $145,000.0 - **Contract:** Permanent contract - **Skills:** Query Performance, HTML, Java (Programming Language), JavaScript (Programming Language), Agile Methodology, Amazon Web Services, Amazon S3, Confluence, JIRA, Configuration Management Databases, Data Architecture, Data Validation, Extract Transform Load (ETL), Data Security, Data Systems, Data Warehousing, DevOps, Elasticsearch, Apache Hadoop, Python (Programming Language), Network Security, OpenShift, Scrum Methodology, Software Tools, Logstash, Ansible, Prometheus, Shell Script, SQL Databases, Systems Integration, Computer Network Operations, Data Ingestion, ReactJS, Snowflake, Grafana, Database Optimization, Git, Data Lakes, Kubernetes, Infrastructure Automation Frameworks, Information Technology, Apache Kafka, Bitbucket, Data Management, Puppet, Kibana, Software Version Control, Data Pipelines, Confluent, Amazon Redshift - **Published:** September 25, 2026 - **Apply:** https://www.thejobnetwork.com/job/9a54f24c-6c40-4272-8a6e-ad7f7f0dc1a0/data-engineering-software-developer ## About the Role * Active DoD TS/SCI security clearance. Ability to pass additional customer suitability screening(s) prior to start. * Current Security+ or equivalent/higher * Bachelor's degree in Computer Science, Engineering, or related technical discipline and 8+ years of relevant experience. * Hands-on experience designing, building, and maintaining data pipelines (ETL/ELT) and integrating multiple, disparate data sources. * Experience with data warehouse and/or data lake technologies (e.g., AWS Redshift, S3, Hadoop, Snowflake, or similar). * Proficiency with data engineering tools and languages such as Python, Java, SQL, and shell scripting. * Experience with Elastic Stack (Elasticsearch, Logstash, Kibana) and/or Kafka for data ingestion and processing. * Familiarity with network operations data (logs, metrics, events, ticketing, CMDB) and related data models. * Experience with Linux/UNIX system administration and automation. * Knowledge of data security, access controls, and compliance frameworks (DoD, DISA, RMF, STIGs). * Experience with CI/CD pipelines, containerized pipelines, version control (Git, Bitbucket), and DevOps practices., * Experience with DISA, DISN, or other DoD network environments, including developing and deploying software applications that meet DoD security standards (e.g., STIGs), and knowledge of network security, encryption, and access controls in classified environments. * Familiarity with Kubernetes deployment, platform upgrades, patching, configuration management tools (Ansible, Puppet, Chef), and monitoring, alerting, and observability tools (Prometheus, Grafana, Elastic) * Strong understanding and practical experience with Agile methodologies (Scrum, SAFe), and related tools such as Atlassian JIRA and Confluence. ## Description * Designs, builds, and maintains scalable, reliable data systems and pipelines to ingest, process, and transform large, complex, and disparate data sources for analytics and reporting. * Unifies and integrates data from multiple network operations systems into a consistent, accessible platform, ensuring data quality, accuracy, security, and compliance with DoD and DISA requirements. * Implements solutions using Confluent Kafka, Elastic Stack, AWS, and Red Hat OpenShift (Kubernetes), including creating Kafka, Elastic, and Logstash pipelines and supporting Kibana visualizations and dashboards with React, JavaScript, and HTML. * Develops and manages data warehouses and data lakes to support analytics, reporting, and operational dashboards, optimizing infrastructure for performance, scalability, and cost-effectiveness through automation and best practices. * Continually analyze and optimize ingestion throughput, query performance, indexing strategies, and storage efficiency across Elastic and Kafka platforms. * Automates data-related tasks such as ETL/ELT processes, data validation, cleansing, monitoring, and supports CI/CD pipelines for automated build, test, and deployment. * Collaborates with data analysts, visualization engineers, and other stakeholders to deliver integrated, actionable data solutions, and documents data architecture, integration patterns, and operational procedures. * Troubleshoots and resolves issues related to data ingestion, processing, and platform performance, storage, memory, partitioning, and cluster performance. ## Related Videos - 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